基于反射高光谱快速、无损的检测优势,以苏北沿海滩涂地区不同成陆年代土壤作为光谱信息源,应用偏最小二乘回归(PLSR)方法,研究了原始反射光谱(REF)、微分光谱(FDR)、反射率倒数的对数(lg(1/R))和波段深度(BD)对不同成陆年代土壤有机质含量的预测精度.结果表明,不同成陆年代土壤有机质含量预测的最佳光谱指标存在差异.REF是构建总体样本有机质含量PLSR预测模型的最佳光谱指标,均方根误差(RMSE)和相关系数(r)分别为2.7231和0.8701;FDR是预测成陆千年土壤样本有机质含量的最佳光谱指标,RMSE和r分别为2.0110和0.9436:BD所构建的成陆百年土壤有机质含量的PLSR预测模型为最优,RMSE和r分别为2.7051和0.8770.相关分析表明,可见光波段、以1400 nm为中心及1 900～2 450 am的红外波段是估算土壤有机质含量的最佳波段.%Based on the advantage of rapid and non-destructive testing of hyperspectral reflectance compared with conventional methods, the hyperspectral models for predicting soil organic matter (SOM) content of different pedogenic time by partial least square regression (PLSR) was conducted in this study. Besides original spectra, several spectral indices were also calculated, including first derivative reflectance spectra (FDR), inverse-log spectra (lg(l/R)) and band depth (BD). The root mean square error (RMSE) and correlation coefficient (r) were used to validate the models. The results show that there is a difference in spectral indices for construct optimal model. REF is the optimal index of building PLSR model, which RMSE and r is 2.7231 and 0.8701, respectively, for predicting SOM content of overall samples. FDR and BD are better index for predicting SOM content form in millennium and century scales, r is 0.9436 and 0.8770, respectively. Correlation analysis shows that visible light region, near infrared that centered in 1 400 nm, and ranged in 1 900-2 450 nm is optimal band for predicting SOM content.
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